Triple
T17040244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | former Laecken-Halle of Leiden |
E413426
|
entity |
| Predicate | nameInDutch |
P13254
|
FINISHED |
| Object |
Lakenhal
Lakenhal is a historic museum in Leiden, Netherlands, housed in a former cloth hall and known for its collection of Dutch Golden Age art.
|
E1245907
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lakenhal | Statement: [former Laecken-Halle of Leiden, nameInDutch, Lakenhal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakenhal Context triple: [former Laecken-Halle of Leiden, nameInDutch, Lakenhal]
-
A.
Rivenhall
Rivenhall is a village in Essex, England, notable for hosting the headquarters of the Essex County Fire and Rescue Service.
-
B.
Eschenlaine
Eschenlaine is a small river in Bavaria, Germany, that serves as a tributary of the Loisach.
-
C.
Hallerowo
Hallerowo is a district of the seaside town Władysławowo in northern Poland, known for its coastal location on the Baltic Sea.
-
D.
Mainbernheim
Mainbernheim is a small historic town in the Franconian wine-growing region of northern Bavaria, Germany.
-
E.
Haldenstein
Haldenstein is a small Swiss village in the canton of Graubünden, known in architecture circles as the longtime base of renowned architect Peter Zumthor.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lakenhal Triple: [former Laecken-Halle of Leiden, nameInDutch, Lakenhal]
Generated description
Lakenhal is a historic museum in Leiden, Netherlands, housed in a former cloth hall and known for its collection of Dutch Golden Age art.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lakenhal Target entity description: Lakenhal is a historic museum in Leiden, Netherlands, housed in a former cloth hall and known for its collection of Dutch Golden Age art.
-
A.
Rivenhall
Rivenhall is a village in Essex, England, notable for hosting the headquarters of the Essex County Fire and Rescue Service.
-
B.
Eschenlaine
Eschenlaine is a small river in Bavaria, Germany, that serves as a tributary of the Loisach.
-
C.
Hallerowo
Hallerowo is a district of the seaside town Władysławowo in northern Poland, known for its coastal location on the Baltic Sea.
-
D.
Mainbernheim
Mainbernheim is a small historic town in the Franconian wine-growing region of northern Bavaria, Germany.
-
E.
Haldenstein
Haldenstein is a small Swiss village in the canton of Graubünden, known in architecture circles as the longtime base of renowned architect Peter Zumthor.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f6a0c08190a838279b83b55b72 |
completed | April 18, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b5ceb048190a7f6cf2361360f90 |
completed | May 10, 2026, 11:57 p.m. |
| NEDg | Description generation | batch_6a011c13076c8190970abfb0e2d3a13c |
completed | May 11, 2026, midnight |
| NED2 | Entity disambiguation (via description) | batch_6a011c8afb608190b51c7a4c9ccaa0a5 |
completed | May 11, 2026, 12:02 a.m. |
Created at: April 10, 2026, 5:33 a.m.